Create PROMETHEUS.md

PROMETHEUS.md

@@ -0,0 +1,54 @@
+Kubecost allows you to export pricing data to Prometheus and then write custom queries to gain cost insights. Below are instructions for accomplishing this.
+
+## Configuration
+
+After deploying the Kubecost model (see [README](README.md) for more info on installation), configure Prometheus to scrape the `/metrics` endpoint exposed by Kubecost. Below is a sample scrape config:
+
+```
+- job_name: kubecost
+  honor_labels: true
+  scrape_interval: 1m
+  scrape_timeout: 10s
+  metrics_path: /metrics
+  scheme: http
+  static_configs:
+  - targets:
+    - kubecost-cost-analyzer.kubecost:9003
+``` 
+
+## Example queries
+
+Below are a set of sample queries that can be run after Prometheus begins ingesting Kubecost data:
+
+__Calculate cost of running each container (as measured over last 24 hours)__
+
+```
+avg_over_time(container_memory_allocation_bytes[24h]) * on(instance) group_left() avg_over_time(node_ram_hourly_cost[24h])  / 1024 / 1024 / 1024
++ 
+avg_over_time(container_cpu_allocation[24h]) * on(instance) group_left() avg_over_time(node_cpu_hourly_cost[24h])   
+```
+
+__Get memory cost for *default* namespace (measured over the last week)__
+
+```
+sum(
+  avg_over_time(container_memory_allocation_bytes{namespace="default"}[24h]) 
+  * 
+  on(instance) group_left() avg_over_time(node_ram_hourly_cost[24h])  / 1024 / 1024 / 1024
+) by (namespace)
+```
+
+__Monthly cost of currently provisioned nodes__
+
+```
+sum(node_total_hourly_cost) * 730
+```
+
+
+## Available Metrics
+
+* node_cpu_hourly_cost
+* node_ram_hourly_cost
+* node_total_hourly_cost
+* container_memory_allocation_bytes
+* container_cpu_allocation